Download Respiratory Tract Samples, Viral Load, and

MAJOR ARTICLE
Respiratory Tract Samples, Viral Load, and
Genome Fraction Yield in Patients With Middle
East Respiratory Syndrome
Ziad A. Memish,1 Jaffar A. Al-Tawfiq,5,10 Hatem Q. Makhdoom,2,6,8,9 Abdullah Assiri,1 Raafat F. Alhakeem,1 Ali Albarrak,3
Sarah Alsubaie,4 Abdullah A. Al-Rabeeah,1 Waleed H. Hajomar,2,6,8,9 Raheela Hussain,2,6,8,9 Ali M. Kheyami,2,6,8,9
Abdullah Almutairi,2,6,8,9 Esam I. Azhar,7 Christian Drosten,11 Simon J. Watson,12 Paul Kellam,12 Matthew Cotten,12
and Alimuddin Zumla1,13
1
Global Centre for Mass Gatherings Medicine and Ministry of Health, Riyadh, Kingdom of Saudi Arabia and College of Medicine, Alfaisal University, 2Regional
Laboratory, Ministry of Health, 3Prince Sultan Military Medical City, 4Pediatric Infectious Diseases, King Saud University, Riyadh, 5Saudi Aramco Medical
Services Organization, Dhahran, 6Regional Laboratory, Ministry of Health, 7Special Infectious Diseases Agents Unit, King Fahad Medical Research Center, King
Abdualziz University, Jeddah, 8Regional Laboratory, Ministry of Health, Madinah, and 9Regional Laboratory, Ministry of Health, Dammam, Kingdom of Saudi
Arabia; 10Indiana University School of Medicine, Indianapolis; 11Institute of Virology, University of Bonn Medical Center, Germany; and 12Wellcome Trust
Sanger Institute, Hinxton, and 13Division of Infection and Immunity, University College London (UCL), and UCL Hospitals National Health Service Foundation
Trust, United Kingdom
Background. Analysis of clinical samples from patients with new viral infections is critical to confirm the diagnosis, to specify the viral load, and to sequence data necessary for characterizing the viral kinetics, transmission, and
evolution. We analyzed samples from 112 patients infected with the recently discovered Middle East respiratory syndrome coronavirus (MERS-CoV).
Methods. Respiratory tract samples from cases of MERS-CoV infection confirmed by polymerase chain reaction
(PCR) were investigated to determine the MERS-CoV load and fraction of the MERS-CoV genome. These values
were analyzed to determine associations with clinical sample type.
Results. Samples from 112 individuals in which MERS-CoV was detected by PCR were analyzed, of which 13
were sputum samples, 64 were nasopharyngeal swab specimens, 30 were tracheal aspirates, and 3 were bronchoalveolar lavage specimens; 2 samples were of unknown origin. Tracheal aspirates yielded significantly higher
MERS-CoV loads, compared with nasopharyngeal swab specimens (P = .005) and sputum specimens (P = .0001).
Tracheal aspirates had viral loads similar to those in bronchoalveolar lavage samples (P = .3079). Bronchoalveolar
lavage samples and tracheal aspirates had significantly higher genome fraction than nasopharyngeal swab specimens
(P = .0095 and P = .0002, respectively) and sputum samples (P = .0009 and P = .0001, respectively). The genome yield
from tracheal aspirates and bronchoalveolar lavage samples were similar (P = .1174).
Conclusions. Lower respiratory tract samples yield significantly higher MERS-CoV loads and genome fractions
than upper respiratory tract samples.
Keywords. Middle East; MERS-CoV; RT-PCR; molecular; diagnosis; coronavirus; clinical; screening; viral load;
Ct value; genome fraction.
A range of clinical specimens from patients with respiratory tract infections (RTIs) [1–3] are sent to the
Received 28 March 2014; accepted 6 May 2014; electronically published 15 May
2014.
Correspondence: Ziad A. Memish, MD, FRCP(Can), FRCP(Edin), FRCP(Lond), FACP,
WHO Collaborating Center for Mass Gathering Medicine, Ministry of Health, Riyadh
11176, Kingdom of Saudi Arabia ([email protected]).
The Journal of Infectious Diseases® 2014;210:1590–4
© The Author 2014. Published by Oxford University Press on behalf of the Infectious
Diseases Society of America. All rights reserved. For Permissions, please e-mail:
[email protected].
DOI: 10.1093/infdis/jiu292
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laboratory by clinicians for making a diagnosis and
monitoring disease activity. Sputum and nasopharyngeal swab specimens are commonly used for patients
who are seen as outpatients or at points of care, and
deeper respiratory tract samples, such as tracheal aspirates and bronchoalveolar lavage samples, are frequently obtained from patients who are seriously ill and
require admission to the intensive care unit [1–3]. Analysis of clinical samples of patients with new viral infections is critical to confirm the diagnosis, undertake
genome sequence analysis, and study the transmission dynamics and evolution of the virus [4–9].
The proportion of the virus genome sequence obtained is dependent on collection of good-quality clinical specimens from
relevant disease sites that can yield higher levels of the virus.
Measuring the concentration of viral genome in the patients’
clinical samples (ie, the viral load) during the course of the illness is also important for estimating the period of infectiousness and for defining guidelines on the duration of isolation
precautions. Viral load measurements can also reflect active
replication and are used in severe viral RTIs for monitoring disease activity, clinical progress, response to therapy, cure, and relapse. Studies of diverse viral RTIs have found that maximal
viral shedding occurs in the first few days after onset of symptoms and then declines with time [3, 4, 7, 9]. Thus, depending
on the site of pathology and viral replication, the most appropriate clinical sample for obtaining the maximal viral genome
yield can be ascertained.
Several community- and hospital-based studies of the recently discovered novel Middle East respiratory syndrome coronavirus (MERS-CoV), a novel species of the genus Betacoronavirus
with positive-sense, single-stranded RNA [10, 11], have shown
that infection with this virus is associated with respiratory tract
disease ranging in severity from mild to severe, rapidly fulminant disease in patients with comorbid medical conditions
[11–19]. Although a real-time reverse-transcription polymerase
chain reaction (RT-PCR) technique for detecting MERS-CoV
was developed [20, 21] and approved by the World Health Organization soon after the first case of MERS-CoV infection was
reported from the Kingdom of Saudi Arabia (KSA), in September 2012, there are scant data on the yield of MERS-CoV genome sequences from various respiratory tract specimens.
Molecular studies of viral infections are crucially dependent
on obtaining good-quality clinical specimens yielding adequate
quantities of intact viral nucleic acid for sequence analysis.
We conducted a study of the relationship between respiratory
tract sample type, MERS-CoV genome load, the proportion of
the virus genome sequence obtained using a range of respiratory
tract samples obtained from laboratory-confirmed cases of
MERS-CoV infection reported from the KSA.
through the nostril, parallel to the palate, into the nasopharynx,
and left in place for a few seconds to absorb secretions. All
swabs were placed immediately into sterile tubes containing
2–3 mL of viral transport medium. For lower respiratory tract
samples, 2–3 mL of tracheal aspirates or bronchoalveolar lavage
fluid were obtained and placed into a dry sterile, leak-proof,
screw cap container.
Storage and Transport of Specimens
Transport of specimens was performed as previously described
[19]. In brief, for short periods (≤48 hours) of transport, specimens were kept at 2°C–8°C. If the transport duration was >48
hours, specimens were shipped frozen on dry ice as soon as possible after collection. Each specimen container was labeled with
the patient identifier, specimen type, and the sample collection
date. Packaging was performed to prevent breakage and spillage,
containers were sealed with parafilm and placed in ziplock bags
with sufficient absorbent material to absorb the entire contents
if spillage occurred, and the primary container was placed inside a secondary container [19].
RNA Extraction
RNA extraction was performed as described previously [19],
using the Roche Magna Pure LC (RNA Viral isolation Kit). Sputum samples were pretreated with 2× lysis buffer for 30 minutes
in a shaking incubator. Swabs were placed in lysis buffer. A total
of 200 µL of each sample was added to a MagNA pure LC plate,
which contains 96 wells. Reaction reagents were then loaded
and checked before running the samples according to the manufacturer’s instructions for nucleic acid extraction in a specimen
preparation area.
MERS-CoV PCR Testing
Clinical samples were screened by a real-time RT-PCR amplification test as previously described [20, 21], with amplification
targeting the upstream E region (upE) and the ORF1a for confirmation. Results were considered positive only if both assays
were positive. When the first and second assays were discordant
or if the real-time RT-PCR result was ambiguous, an additional
clinical sample was requested and analyzed.
Genome Extraction and Sequence Generation
METHODS
Collection of Clinical Specimens
The following respiratory tract samples were analyzed for
MERS-CoV load (by determining threshold cycle [Ct] values)
and the proportion of MERS-CoV genome obtained: sputum
samples, nasopharyngeal swab samples, tracheal aspirates, and
bronchoalveolar lavage specimens. Sputum specimens were collected directly into a sterile, leak-proof, screw cap container; nasopharyngeal swabs specimens were collected using sterile,
synthetic (Dacron)–tipped flocked swabs. Swabs were inserted
MERS-CoV deep sequencing was conducted as previously described [22, 23]. The MERS-CoV genome sequences that have
been analyzed have all been published and described previously
[13, 22–24].
Statistical Analyses
MERS-CoV load and genome fraction were recorded for each
set of sputum specimens, nasopharyngeal swab specimens, tracheal aspirates, or bronchoalveolar lavage samples. Standard
box and whisker plots with a median value for each set were calculated for MERS-CoV load and fraction of MERS-CoV
Sample Type and MERS-CoV
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genome obtained. The fraction of MERS-CoV genome obtained
was plotted by sample viral Ct value against sample type. Mann–
Whitney U tests were performed for all comparisons; a P value
of <.05 was considered to be statistically significant.
RESULTS
Respiratory tract samples obtained from 112 individuals with
positive results of real-time RT-PCR for MERS-CoV were analyzed. This set includes 13 sputum samples, 64 nasopharyngeal
swabs, 30 tracheal aspirates, and 3 bronchoalveolar lavage samples. Two samples received by the laboratory had no sample
type indication and were not included in the analysis.
Viral Load Ct Values
A comparison of the MERS-CoV real-time RT-PCR Ct values as a
function of sample type was performed (Figure 1, upper panel).
Table 1 shows the P values for the comparison of sample type
to Ct value. Tracheal aspirates yielded significantly lower MERSCoV Ct values (ie, a higher viral load) than nasopharyngeal
swab specimens (P = .0005) and sputum specimens (P = .0001).
There was no significant difference in viral load Ct values when
tracheal aspirates were compared to bronchoalveolar lavage specimens (P = .3079).
Genome Fraction Values
Figure 1 (lower panel) shows the MERS-CoV genome fraction
obtained from each sample type. Figure 2 shows the correlation
of the fraction of the MERS-CoV genome obtained with the
sample Ct value relative to the sample type. Higher MERSCoV genome fractions were obtained from bronchoalveolar lavage samples and tracheal aspirates than from nasopharyngeal
swab specimens (P = .0095 and P = .0002, respectively) and sputum samples (P = .0009 and P = .0001, respectively; Table 1).
There was no significant difference in genome yield between
tracheal aspirates and bronchoalveolar lavage samples
(P = .1174; Table 1).
DISCUSSION
This study presents the largest data set available to date on molecular analyses of several types of respiratory tract samples and
describes the distribution of the MERS-CoV genome load and
fraction of the virus genome sequence obtained from these samples. Varying amounts of MERS-CoV load and fractions of
MERS-CoV genomes were obtained from all clinical sample
types received from 110 Saudi Arabian patients with MERSCoV infection. When stratified by site of sample origin, samples
from deeper in the respiratory tract (ie, tracheal aspirates and
bronchoalveolar lavage specimens) yielded significantly higher
Figure 1. Clinical sample type and Middle East respiratory syndrome coronavirus (MERS-CoV) threshold cycle (Ct) values. The Ct of real-time reversetranscription polymerase chain reaction, a measurement of MES-CoV viral load (upper panel) or fraction of MERS-CoV genome obtained by deep sequencing
(lower panel) were plotted by clinical sample type (tracheal aspirates [TAs], nasopharyngeal swab specimens [NPs], sputum specimens, and bronchoalveolar
lavage specimens [BALs]). Box and whisker plots were prepared using the Python/Matplotlib box plot module (http://matplotlib.org/examples/
pylab_examples/boxplot_demo.html). Data are for 110 specimens collected through 14 November 2014. Gray boxes indicate the lower to upper quartile
values of each subset, blue lines indicate median values, and whiskers indicate ranges, with outlier points falling above or below 1.5 times the interquartile
range indicated individually.
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Table 1. Statistical Analyses of Clinical Sample Type
Comparisons for Yield of Middle East Respiratory Syndrome
Coronavirus (MERS-CoV) Load and of the MERS-CoV Genome
Fraction
P, Viral Loada
P, Genome Fractionb
TA vs NP
.0005
.0002
TA vs Sputum
.0001
.0001
TA vs BAL
NP vs Sputum
.3079
.0113
.1174
.0092
NP vs BAL
.0298
.0095
Sputum vs BAL
.0074
.0009
Comparison
Abbreviations: BAL, bronchoalveolar lavage fluid; Ct, threshold cycle; NP,
nasopharyngeal swab specimen; TA, tracheal aspirate.
a
Values denote results of the comparison of Ct real-time reverse-transcription
polymerase chain reaction findings, using the Mann–Whitney U test.
b
Values denote results of the comparison of deep sequencing findings, using
the Mann–Whitney U test.
MERS-CoV genome loads and genome sequenced fractions
than samples from other respiratory tract (ie, sputum and nasopharyngeal swab specimens), although samples from all anatomical sites appear to be suitable for viral load determination
and virus genome sequencing studies.
Conventionally, tests to detect viral infections in the respiratory tract are performed on sputum or nasopharyngeal swab
specimens from patients not requiring admission to the intensive care unit [1, 2, 19] and on tracheal aspirates and bronchoalveolar lavage samples from patients in the intensive care unit
[3, 4, 7, 13], and the samples are therefore accessible. A limitation of this study is the lack of multiple samples from multiple
compartments of a single patient. However, given this limitation, it appears that viral load is good predictor of MERSCoV sequencing success.
The viral load in a clinical sample at any given time reflects
the dynamic interaction between MERS-CoV replication and
the ability of the host’s immune system to eliminate the virus.
Thus, MERS-CoV load measurements can be clinically useful
for monitoring disease activity, clinical progress, response to
therapy, and cure, and they can also be used as a marker of
prognosis [7–11]. The ideal approach to determining the most
appropriate clinical sample for making a diagnosis, ascertaining
the viral load, and obtaining the optimal genome fraction requires understanding of the natural history of the viral infection
[9–11]. Data from the severe acute respiratory syndrome (SARS)
epidemic showed low SARS-CoV loads in the upper respiratory
tract and high viral loads in the lower respiratory tract [9–11].
The natural history of SARS-CoV infection was unique in that
test results for nasopharyngeal specimens were often negative
during the first week of infection, and the highest positivity
rates occurred during the second week of illness, peaking at approximately day 10. This allowed definition of which and when
during the course of infection clinical specimens will test
Figure 2. Fraction of the sequenced Middle East respiratory syndrome
coronavirus (MERS-CoV) genome obtained as a function of MERS-CoV
load. Samples were stratified by clinical sample type and the fraction of
MERS-CoV genome obtained by deep sequencing was plotted as a function of the MERS-CoV load ( presented in terms of the threshold cycle [Ct]
value). Data are for 110 specimens collected through 14 November 2014.
Tracheal aspirates (TAs) are indicated by red circles, nasopharyngeal swab
samples (NPs) are indicated with black Xs, sputum samples are indicated
with gray circles, bronchoalveolar lavage samples (BAL) are indicated with
green circles, and samples with an unknown type (n = 2) are indicated with
black crosses.
positive [5, 11]. The low virus detection rate in nasopharyngeal
specimens early in the course of SARS-CoV infection illustrates
the importance of optimal timing of specimen collection and
the optimal specimen type for diagnosis.
Definition of the natural history of the virus may indicate
possible sites in the respiratory tract and other parts of the
body where the virus causes inflammation and damage. In
other common respiratory viral infections, such as influenza,
the viral load peaks soon after the onset of symptoms [4].
There were several features of SARS that distinguished it from
other viral causes of RTIs [7, 11]. The pathogenic potential, natural history, and transmission dynamics of MERS-CoV require
definition before the optimal sample type can be ascertained.
Dipeptidyl peptidase 4 was identified as the receptor for
MERS-CoV [25], and these receptors are expressed on primary
human bronchiolar lung tissue; thus, the virus is able to infect
lower respiratory tract tissues. Gastrointestinal symptoms are
also present in patients infected with MERS-CoV [13].
Diagnostic tests for respiratory viral infections or screening of
close contacts have traditionally been performed on upper respiratory tract samples, particularly nasopharyngeal swab specimens, and it is no different for MERS-CoV. For detecting
MERS-CoV, the choice of the most appropriate respiratory
tract specimen for diagnostic purposes remains to be determined and requires further study of several respiratory tract
sample types obtained at the same time from the same patient.
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Further studies are required to (1) define the natural history of
MERS-CoV infection in humans and the viral load kinetics over
time in various respiratory tract samples; 2) determine MERSCoV shedding in various nonrespiratory clinical sample types,
such as urine, stool, blood, or effusions from the time of infection to recovery or death; and 3) correlate viral load with intensive care unit admission and death as a composite end point.
These data are required to shed further light on MERS-CoV
pathogenesis, ascertain the optimal clinical samples for diagnosis, and guide optimal infection control measures. Viral load
measurements could also serve as biomarkers for monitoring
response to therapy, disease activity, and predict prognosis.
Notes
Acknowledgments. We are grateful to all staff of the Ministry of Health,
Kingdom of Saudi Arabia (KSA); and to Mr Adam Zumla, University College London School of Pharmacy, for kindly providing technical and administrative support.
This study was initiated, designed, and conducted as a major priority
issue under the auspices of The Global Center for Mass Gatherings Medicine (GCMGM), Ministry of Health, KSA. Board members of the GCMGM,
Abdullah Al-Rabeeah (chair), Ziad A Memish (vice chair), Alimuddin
Zumla, Jaffar A. Al-Tawfiq, Abdullah Assiri, Ali Albarrak, and Rafaat AlHakeen, initiated a range of MERS-CoV studies.
H. Q. M., A. Z., J. Al-T., and M. C. collected data on viral load and genome fraction and finalized the database. All KSA authors were involved in
sample collection and patient management. M. C., P. K., and S. J. W. were
responsible for generating the MERS-CoV genome sequences analyzed, and
M. C. developed the figures and tables. Z. A. M., A. Z., H. Q. M., J. Al-T., and
M. C. wrote the first and final drafts of the manuscript. All authors contributed to the finalization of the manuscript.
Financial support. This work was supported by the Saudi Ministry of
Health. The following authors acknowledge the University College London
Hospitals NHS Foundation Trust (to A. Z.); the National Institute of Health
Research, Biomedical Research Centre, UCL Hospitals (to A. Z.); the
EDCTP (to A. Z.); the EC-FW7 (RiD-RTI to A. Z.); the Wellcome Trust
(to P. K., M. C., and S. W.); the European Community Seventh Framework
Programme (FP7/2007-2013), under the projects EMPERIE (grant 223 498
to P. K., M. C., and S. W. and contract 223 498 to C. D.) and ANTIGONE
(contract 278 976 to C. D.); the German Centre for Infection Research (to
C. D.); the German Ministry for Research and Education (to C. D.); and the
German Research Council (grants 01KIO701 and DR 772/3-1 to C. D.).
Potential conflicts of interest. All authors: No reported conflicts.
All authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
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